City of Garland, GIS Department
City of Garland, GIS Department
Selected completed projects completed at the City of Garland, GIS Department
I assisted in developing a geometric network from the existing building and civil work drawings. Different aspects of the network were checked for consistency, including:
The size and type of pipes (RCC, PVC)
The fitting and connection types (Inlet, outlet, intake, outfall, connection)
The direction of flow
Resolving overlapping lines
Lines to be snapped at endpoints
Configuring junctions
References
Engineering Building / Civil Works Drawings
Google Street View
Google Maps, Satellite View
Contour Maps
In collaboration with the city works department, drawing symbols were developed to communicate the size and type of connections while preserving the integrity of the geometric network.
Identify Errors
Errors in the existing geometric network were identified for buildings, the natural and built environment.
Investigate and Define
I used a combination of engineering and city civil work drawings to understand the existing stormwater network and develop connections.
Resolve Connections
Defined rules and dependencies were used to correct the drawing and connectivity errors.
The map shows drive times for 3 proposed sites for fire stations in Garland. In addition to this study, drive times around existing fire stations were also developed to evaluate any gaps in service or coverage. Drive-time analysis was developed by creating service areas and setting the parameters for Travel Mode restrictions: Trucking Time to accommodate larger emergency vehicles, a slower maximum speed to accommodate speed limitations for larger vehicles, and traffic regulations for emergency vehicles.
In this project, a pre-trained ESRI deep learning (DL) model is used to detect swimming pools in the City of Garland within an area consisting of 56 homes. The Object Detection tool from the Deep Learning Toolbox is used. For the area shown, the model ran for approximately 30 minutes and detected 5 swimming pools.
Imagery submitted for analysis.
Detected swimming pools
This project identified high-density areas of low-cost housing in the City of Garland. The Kernel Density tool creates a density mapping of home values under $250K and $200K. Next, the Contour List tool uses a calculated contour interval to only demarcate the target area.
Rental property data for single homes was used to find the percentage of rental properties in each Council District and Block Group. In addition, heat mapping and hotspot analysis were used to identify statistically significant clusters of high or low-density areas of rental properties.
The Traffic Grant Zones were updated and printed for use by the Police Department.
I developed a City of Garland Tapestry Map for internal use using ESRI Data. I used a combination of symbology, labeling, and layout techniques to reduce visual clutter and increase the visibility of the dominant tapestry areas within the City of Garland at the Block Group level.
The ESRI Tapestry Map is a tool that shows demographic and lifestyle data for neighborhoods and areas within the United States. It is produced by ESRI, a leading provider of geographic information systems (GIS) software and services.
The ESRI Tapestry Map divides the United States into 67 distinct lifestyle segments based on demographic and socio-economic data. Each segment is assigned a unique name and characteristics that reflect the dominant lifestyle trends and characteristics of those living there.
Businesses and organizations often use the map to understand better the characteristics and preferences of the people living in a particular area and to target marketing and outreach efforts accordingly. Real estate professionals also use it to help buyers or sellers identify neighborhoods and areas of particular interest based on their lifestyle preferences.
Housing sales contract information is downloaded in spreadsheet format. Houses are geocoded to the correct address, and then the geocoded data is appended to the hosted database.